Evidence map›Paper›PMID 38550613›Full record

ReviewPathogens & immunity2024

Chimeric Antigen Receptor (CAR)-T Cell Therapy for Non-Hodgkin's Lymphoma.

Maria Florencia Giraudo, Zachary Jackson, Indrani Das, Olubukola M Abiona, David N Wald

Open access · diamondAbstract readReview
In one paragraph

Review in Pathogens & immunity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Advances in nano-immunotherapy for hematological malignancies.Experimental hematology & oncology · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Maria Florencia GiraudoDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio.
Zachary JacksonDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio.
Indrani DasDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio.
Olubukola M AbionaDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio.
David N WaldDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio.
Case Western Reserve University · US

Funding

Immunology Training Program-PredoctoralT32AI089474 · NIAID · CASE WESTERN RESERVE UNIVERSITY · PI COBB, BRIAN A · 2010 to 2025
$3.4M
NIAID NIH HHS T32 AI089474
6 · The paper itself

Abstract

This review focuses on the use of chimeric antigen receptor (CAR)-T cell therapy to treat non-Hodgkin's lymphoma (NHL), a classification of heterogeneous malignant neoplasms of the lymphoid tissue. Despite various conventional and multidrug chemotherapies, the poor prognosis for NHL patients remains and has prompted the utilization of groundbreaking personalized therapies such as CAR-T cells. CAR-T cells are T cells engineered to express a CAR that enables T cells to specifically lyse tumor cells with extracellular expression of a tumor antigen of choice. A CAR is composed of an extracellular antibody fragment or target protein binding domain that is conjugated to activating intracellular signaling motifs common to T cells. In general, CAR-T cell therapies for NHL are designed to recognize cellular markers ubiquitously expressed on B cells such as CD19

Indexed as

CAR-TCell TherapyChimeric Antigen ReceptorsImmunotherapyLymphoma

Identifiers

PMID38550613
PMCPMC10972674
OpenAlexW4392878640

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.